![]() For this reason, it makes sense *not* to bundle PyFFI (but I'm sure one could argue the other way around too :) ). ![]() I could also include PyFFI with the package, however any modder who uses these scripts will likely also have PyFFI installed in his Python install as PyFFI can also be used as a standalone tool for doing all sorts of things with nif files (and other files). They should run on any version of blender >= 2.45 with python >= 2.5 (but not p圓k of course), but currently testing happens mostly on 2.49a with Python 2.6. The scripts are still under active development and have a fairly aggressive release schedule, so the general idea is for blender to ship a stable version of them, and that enthusiasts can download the latest version from the niftools site if they want. Additional files not necessary just to run the scripts are not in the zip but are are available here (changelog, readme, test suite, nsis installer code. I was asked to submit my nif scripts here attached is a zip containing the essentials. Experiments using wearable sensing data for multi-class HAR is used, to test the efficacy of the new methodology VFDT+MR, in comparison to a classical data stream mining algorithm VFDT alone.Script name: Import & Export NIF File Format (.nif &. Think about the extreme postures of how a person collapses and free falling from height. For examples, squatting involves actions in between standing and sitting, falling straight down is a sequence of standing, possibly body tiling or curling, bending legs, squatting and crashing down on the floor and there may be totally new (unseen) actions beyond the training instances when it comes to classifying " abnormal " human behaviours. ![]() In HAR, most misclassified instances are those belonging to ambiguous movements. Specifically, a new technique namely Misclassified Recall (MR) which is a post-processing step for relearning a new concept, is formulated. In this paper, an improved version of Very Fast Decision Tree (VFDT) is proposed which makes use of misclassified results for post-learning. ![]() ![]() One of the emerging applications of HAR is to monitor needy people such as elders, patients of disabled, or undergoing physical rehabilitation, using sensing technology. Human activity recognition (HAR) has been a popular research topic, because of its importance in security and healthcare contributing to aging societies. ![]()
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